期刊
EXPERT SYSTEMS WITH APPLICATIONS
卷 41, 期 7, 页码 3157-3167出版社
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.eswa.2013.11.014
关键词
Multi-objective optimization; PSO; Reliability optimization; Intuitionistic fuzzy set theory; Membership functions
In designing phase of systems, design parameters such as component reliabilities and cost are normally under uncertainties. This paper presents a methodology for solving the multi-objective reliability optimization model in which parameters are considered as imprecise in terms of triangular interval data. The uncertain multi-objective optimization model is converted into deterministic multi-objective model including left, center and right interval functions. A conflicting nature between the objectives is resolved with the help of intuitionistic fuzzy programming technique by considering linear as well as the nonlinear degree of membership and non-membership functions. The resultants max-min problem has been solved with particle swarm optimization (PSO) and compared their results with genetic algorithm (GA). Finally, a numerical instance is presented to show the performance of the proposed approach. (C) 2013 Elsevier Ltd. All rights reserved.
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